{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "22f037ad-d2ec-485a-9798-9ac8bf350480",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "# Anscombe's Quartet\n",
    "\n",
    "The raw data has four series. The correlation coefficients are high.\n",
    "Visualization shows that a simple linear regression model is misleading.\n",
    "\n",
    "## Raw Data for the Series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "a79d2991-7893-4cb2-b001-b55888c68efc",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "import json\n",
    "from pathlib import Path\n",
    "from pydantic import BaseModel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "99a55c73-67ad-4ce0-9faf-7921a179e5f2",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "class Pair(BaseModel):\n",
    "    x: float\n",
    "    y: float\n",
    "\n",
    "class Series(BaseModel):\n",
    "    series: str\n",
    "    data: list[Pair]\n",
    "\n",
    "    @property\n",
    "    def x(self) -> list[float]:\n",
    "        return [p.x for p in self.data]\n",
    "        \n",
    "    @property\n",
    "    def y(self) -> list[float]:\n",
    "        return [p.y for p in self.data]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "9f5030f1-f7bb-4254-a829-86cf198eed9c",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "source = Path.cwd().parent.parent / \"data\" / \"anscombe.json\"\n",
    "with source.open() as source_file:\n",
    "    json_document = json.load(source_file)\n",
    "    source_data = (Series.model_validate(s) for s in json_document)\n",
    "    quartet = {s.series: s for s in source_data}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "df4a3189-55df-42f0-ad86-0b61e41cedba",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Series(series='I', data=[Pair(x=10.0, y=8.04), Pair(x=8.0, y=6.95), Pair(x=13.0, y=7.58), Pair(x=9.0, y=8.81), Pair(x=11.0, y=8.33), Pair(x=14.0, y=9.96), Pair(x=6.0, y=7.24), Pair(x=4.0, y=4.26), Pair(x=12.0, y=10.84), Pair(x=7.0, y=4.82), Pair(x=5.0, y=5.68)])"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "quartet['I']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "13108efb-7c10-4250-8c24-4bff9d53f66c",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Series(series='IV', data=[Pair(x=8.0, y=6.58), Pair(x=8.0, y=5.76), Pair(x=8.0, y=7.71), Pair(x=8.0, y=8.84), Pair(x=8.0, y=8.47), Pair(x=8.0, y=7.04), Pair(x=8.0, y=5.25), Pair(x=19.0, y=12.5), Pair(x=8.0, y=5.56), Pair(x=8.0, y=7.91), Pair(x=8.0, y=6.89)])"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "quartet['IV']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0c285d5b-eb40-4956-a586-4c07d08266f8",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "## Visualization of each series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "512046c8-a3a7-43dc-9f70-456835485651",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "from matplotlib import pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "a17c2207-792f-4043-b11d-cbd3060f9445",
   "metadata": {
    "editable": true,
    "scrolled": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = [p.x for p in quartet['I'].data]\n",
    "y = [p.y for p in quartet['I'].data]\n",
    "plt.scatter(x, y)\n",
    "plt.title(f\"Series {quartet['I'].series}\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "a778c6ad-42a9-4eac-9806-7afc01a62303",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(layout='tight')\n",
    "for n, series in enumerate(quartet.values(), start=1):\n",
    "    title = f\"Series {series.series}\"\n",
    "    plt.subplot(2, 2, n)\n",
    "    plt.scatter(series.x, series.y)\n",
    "    plt.title(title)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "57c0034b-57ee-4e0b-8ebc-491acaef6fbe",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
